Machine Learning and Knowledge Extraction, Volume 7, Issue 1

This work deals with the investigation and optimization of the MINDWALC node classification algorithm with a focus on its ability to learn human-interpretable decision trees from knowledge graph databases. For this, we introduce methods to optimize M...

Generative large language models (LLMs) have revolutionized the development of knowledge-based systems, enabling new possibilities in applications like ChatGPT, Bing, and Gemini. Two key strategies for domain adaptation in these systems are Domain-Sp...

Adversarial training, a widely used technique for fortifying the robustness of machine learning models, has seen its effectiveness further bolstered by modifying loss functions or incorporating additional terms into the training objective. While thes...

The integration of machine learning (ML) with big data has revolutionized industries by enabling the extraction of valuable insights from vast and complex datasets. This convergence has fueled advancements in various fields, leading to the developmen...

This study introduces the Pixel-Level Interpretability (PLI) model, a novel framework designed to address critical limitations in medical imaging diagnostics by enhancing model transparency and diagnostic accuracy. The primary objective is to evaluat...

Basketball players are traditionally classified into five positions. This study examines the correlation between player performance, game statistics, and designated positions. It also explores how statistical contributions have evolved over time. Mac...

Transformer models produce advanced text representations that have been used to break through the hard challenge of natural language understanding. Using the Transformer’s attention mechanism, which acts as a language learning memory, trained o...

This study investigates the relationship between consumer personality traits, specifically openness, and responses to product designs. Consumers are categorized based on their levels of openness, and their affective responses to nine vase designs, va...

Representing and interpreting human opinions within an unstructured framework is inherently complex. Hesitant fuzzy linguistic term sets offer a comprehensive context that facilitates a nuanced understanding of diverse perspectives. This study introd...

Interdisciplinary research (IDR) is essential for addressing complex global challenges that surpass the capabilities of any single discipline. However, measuring interdisciplinarity remains challenging due to conceptual ambiguities and inconsistent m...